Data Set ID: 
NSIDC-0736

Weather Research and Forecasting (WRF) North American Mountain Snow Data, Version 1

This data set consists of modeled snow water equivalent (SWE) data for 10 mountain ranges in North America, simulated by the Weather Research and Forecasting (WRF) regional climate model.

This is the most recent version of these data.

Version Summary: 

New data set.

STANDARD Level of Service

Data: Data integrity and usability verified

Documentation: Key metadata and user guide available

User Support: Assistance with data access and usage; guidance on use of data in tools

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Parameter(s):
  • SNOW/ICE > SNOW WATER EQUIVALENT
Data Format(s):
  • NetCDF
Spatial Coverage:
N: 69.7, 
S: 31.9, 
E: -56.8, 
W: -168.2
Platform(s):MODELS
Spatial Resolution:
  • 9 km x 9 km
Sensor(s):NOT APPLICABLE
Temporal Coverage:
  • 1 October 2004 to 30 June 2013
Version(s):V1
Temporal Resolution1 dayMetadata XML:View Metadata Record
Data Contributor(s):Melissa Wrzesien

Geographic Coverage

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As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Wrzesien, M. and M. Durand. 2018. Weather Research and Forecasting (WRF) North American Mountain Snow Data, Version 1. [Indicate subset used]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.5067/W4JHZBCRCNLX. [Date Accessed].
Created: 
20 August 2018
Last modified: 
10 October 2018

Data Description

This data set provides simulated snow water equivalent (SWE) for 10 mountain ranges within North America at a spatial resolution of 9 km. The data were simulated using the Weather Research and Forecasting (WRF) regional climate model and are presented as 10 individual WRF simulations between 2004 and 2013 for each of the mountain ranges. Each simulation covers the time period from 01 October from one year to 30 June of the following year; i.e., the winter accumulation and spring melt seasons. See Table 1 for a list of mountain ranges and the corresponding simulation years.

Parameters

The parameter presented in this data set is SWE in millimeters.

File Information

Format

The data are in netCDF (.nc) format.

File Contents

Each netCDF file contains SWE in millimeters, elevation in meters, latitude and longitude coordinates, time, and a data mask. The purpose of the mask, which consists of values equal to 1, is to select the mountain ranges within each domain. Figure 1 shows peak (i.e., maximum) SWE for all mountain ranges from all representative years.

Figure 1. Compilation of peak SWE (in mm) from each WRF simulation, i.e., for all mountain ranges in this data set. Figure adapted from Wrzesien et al. (2018).

Directory Structure

Data are available via HTTPS from the following directory:

https://daacdata.apps.nsidc.org/pub/DATASETS/nsidc0736_WRF_swe_v01/

Within this directory, there are 10 files that correspond to the different mountain ranges on the North American continent and span different time periods. Table 1 lists the different mountain ranges and corresponding simulation years; Figure 2 provides the locations of the mountain ranges.

Table 1. Mountain Ranges and Corresponding Simulation Years

Mountain Range
(x) = Number in Figure 2

File Name Designation Simulation Years
Alaska (1) alaska 2007–2008
Appalachian (2) app 2004–2005
Brooks (3) brooks 2004–2005
Cascades (4) cascades 2008–2009
Coast (5) coast 2004–2005
Mackenzie (7) mackenzie 2012–2013
Rockies, Canada (8) nrockies 2011–2012
Sierra Nevada (9) sierra 2008–2009
Rockies, USA (6, 10)* srockies 2005–2006
Torngat (11) torngat 2007–2008

*Note: The Rockies, USA, range also includes the Great Basin range (mountain range number 6 in Figure 2).

Figure 2. Individual mountain ranges from the WRF simulations. The numbers on the map correspond to the numbers in parentheses in Table 1. Figure from Wrzesien et al. (2018).

Naming Convention

The data files are named according to the following convention and as described in Table 2.

Example file names:

alaska_2007_2008_swe_v01.nc

File naming convention:

mtnrange_YYYY_yyyy_swe_v01.nc

Table 2. File Naming Convention
Variable Description
mtnrange Mountain range; e.g., alaska = Alaska (see Table 1)
YYYY_yyyy Simulation start and end years; e.g., 2007_2008 (see Table 1)
swe Data set parameter; swe = snow water equivalent
v01 Data set version; v01 = Version 1

File Size

The total file volume is approximately 2.1 GB.

Spatial Information

Coverage

The mountain ranges simulated in this data set fall within the following geographical boundaries:

Northernmost latitude: 69.7° N
Southernmost latitude: 31.9° N
Easternmost longitude: 56.8° W
Westernmost longitude: 168.2° W

Resolution

The data are gridded at a horizontal resolution of 9 km x 9 km.

Geolocation

All 10 WRF simulations in this data set were run using a Lambert Conformal Conic Projection. However, different true latitude and standard longitude points were chosen for each of the simulated domains. Thus, the coordinate system information varies between the individual domains and for each file.

Temporal Information

Coverage

01 October 2004 to 30 June 2013

Resolution

Daily

Data Acquisition and Processing

Acquisition and Processing Steps

The reader is referred to Wrzesien et al. (2018) for details on the processing steps used to generate these data.

Quality, Errors, and Limitations

Due to the computational demands of simulating a model at 9 km resolution across the whole North American continent, it was not possible to perform one continuous multiple-year simulation to produce a multi-decadal climatology. Instead, a new method called "representative-climatology" was introduced, which approximates a traditional climatology by simulating separate model domains for a single representative year specific to each mountain range (see Table 1). One caveat of the representative-climatology method is that the SWE estimates were derived from simulating individual years instead of using a more traditional multi-decadal climatology. Wrzesien et al. (2018) performed an analysis to assess the suitability of this approach and found that for three independent global data products, the total SWE across individual representative years for each range fell within ±7% of the 30-year average. Thus, this approach reasonably approximates a continental climatology at a fraction of the computational cost.

Instrumentation

The numeric model used in this study is WRF, Version 3.6, coupled to the Noah-MP land surface model (Niu et al., 2011). Simulations were run as one-way nested domains, with an outer and an inner domain. The outer domain, which has a spatial resolution of 27 km, forces the inner 9 km domain. Only the 9 km resolution data are presented in this data set. The outermost boundaries were forced by the ERA-Interim reanalysis (Dee et al., 2011), which was chosen as the forcing data set since it covers all of the North American continent. More information on the WRF model and the simulations can be found in Wrzesien et al. (2018).

Software and Tools

For a list of tools for reading or viewing netCDF files, please see the NetCDF Resources at NSIDC: Software and Tools web page.

Related Data Sets

Related Websites

Contacts and Acknowledgments

Melissa Wrzesien
Department of Geological Sciences
University of North Carolina at Chapel Hill
Chapel Hill, NC, USA

Acknowledgments

This work was supported in part by the NASA Earth and Space Science Fellowship NNX14AT34H and the NASA New Investigator Grant NNX13AB63G. High‐performance computing support came from the NASA High‐End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by the National Science Foundation grant ACI‐1053575.

References

Dee, D. P., S. M. Uppala, A. J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, et al. (2011). The ERA-interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553–597. doi: https://doi.org/10.1002/qj.828

Hall, D. K., V. V. Salomonson, and G. A. Riggs (2006). MODIS/Terra snow cover monthly L3 global 0.05Deg CMG. Version 5. MOD10CM. Boulder, CO: National Snow and Ice Data Center. doi: https://doi.org/10.5067/IPPLURB6RPCN

Niu, G. Y., Z.-L. Yang, K. E. Mitchell, F. Chen, M. B. Ek, M. Barlage, M., et al. (2011). The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research, 116, D12109. doi: https://doi.org/10.1029/2010JD015139

Wrzesien, M. L., M. T. Durand, T. M. Pavelsky, S. B. Kapnick, Y. Zhang, J. Guo, and C. K. Shum (2018). A new estimate of North American mountain snow accumulation from regional climate model simulations. Geophysical Research Letters, 45(3), 1423–1432. doi: https://doi.org/10.1002/2017GL076664

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